Evidence map›Paper›PMID 39191743›Full record

ArticleNature communications2024

The temporal dynamics of group interactions in higher-order social networks.

Iacopo Iacopini, Márton Karsai, Alain Barrat

Abstract read
In one paragraph

Article in Nature communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

21 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Homophily within and across groups.Nature communications · 2025
    Article
  10. Review
  11. Article
  12. Article
  13. Promoting collective cooperation through temporal interactions.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  14. Drivers of cooperation in social dilemmas on higher-order networks.Journal of the Royal Society, Interface · 2025
    Article
  15. Article
  16. Article
  17. Article
  18. Not your private tête-à-tête: leveraging the power of higher-order networks to study animal communication.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2024
    Article
  19. Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Iacopo IacopiniNetwork Science Institute, Northeastern University London, London, E1W 1LP, United Kingdom. iacopo.iacopini@nulondon.ac.uk.ORCID 0000-0001-8794-6410
Márton KarsaiDepartment of Network and Data Science, Central European University, A-1100, Vienna, Austria.ORCID 0000-0001-5382-8950
Alain BarratAix Marseille Univ, Université de Toulon, CNRS, CPT, Turing Center for Living Systems, Marseille, France.ORCID 0000-0001-8683-269X

Funding

Agence Nationale de la Recherche (French National Research Agency) ANR-19-CE46-0008Austrian Science Fund (Fonds zur Förderung der Wissenschaftlichen Forschung) FWF I 5205-NEC | Horizon 2020 Framework Programme (EU Framework Programme for Research and Innovation H2020) H2020-871042James S. McDonnell Foundation (McDonnell Foundation) https://doi.org/10.37717/2020-1516
6 · The paper itself

Abstract

Representing social systems as networks, starting from the interactions between individuals, sheds light on the mechanisms governing their dynamics. However, networks encode only pairwise interactions, while most social interactions occur among groups of individuals, requiring higher-order network representations. Despite the recent interest in higher-order networks, little is known about the mechanisms that govern the formation and evolution of groups, and how people move between groups. Here, we leverage empirical data on social interactions among children and university students to study their temporal dynamics at both individual and group levels, characterising how individuals navigate groups and how groups form and disaggregate. We find robust patterns across contexts and propose a dynamical model that closely reproduces empirical observations. These results represent a further step in understanding social systems, and open up research directions to study the impact of group dynamics on dynamical processes that evolve on top of them.

Indexed as

Social NetworkingAdolescentAdultChildFemaleGroup ProcessesHumansInterpersonal RelationsMaleModels, TheoreticalSocial InteractionStudentsYoung Adult

Identifiers

PMID39191743
PMCPMC11349943

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.